Effects of Temperature and Blinking on Contact Lens Dehydration of Contemporary Soft Lens Materials Using an In Vitro Blink Model
Why this work is in the frame
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Bibliographic record
Abstract
Purpose: The purpose of this study was to evaluate the effects of temperature and blinking on contact lens (CL) dehydration using an in vitro blink model. Methods: Three silicone hydrogel (delefilcon A, senofilcon A, and comfilcon A) and two conventional hydrogel (etafilcon A and omafilcon A) CL materials were evaluated at 1 and 16 hours. The water content (WC) of the CLs was measured using a gravimetric method. Lenses were incubated on a blink model, internally heated to achieve a clinically relevant surface temperature of 35°C. An artificial tear solution (ATS) was delivered to the blink model at 4.5 µL/min with a blink rate of 6 blinks/min. A comparison set of lenses were incubated in a vial containing either 2 mL of ATS or phosphate-buffered saline (PBS) at 35°C. Results: Increasing temperature to 35°C resulted in a decrease in WC for all tested CLs over time (P ≤ 0.0052). For most CLs, there was no significant difference in WC over time between ATS or PBS in the vial (P > 0.05). With the vial system, WC decreased and plateaued over time. However, on the blink model, for most CLs, the WC significantly decreased after 1 hour but returned toward initial WC levels after 16 hours (P > 0.05). Conclusions: The reduction in WC of CLs on the eye is likely due to both an increase in temperature and dehydration from air exposure and blinking. Translational Relevance: This study showed that the novel, heated, in vitro blink model could be used to provide clinical insights into CL dehydration on the eye.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it